Modelling Economic Capital: Practical Credit-Risk Methodologies, Applications, and Implementation Details
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer International Publishing AG
2022
|
| Ausgabe: | 1st ed |
| Schriftenreihe: | Contributions to Finance and Accounting Series
|
| Schlagworte: | |
| Online-Zugang: | HWR01 |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 Online-Ressource (841 Seiten) |
| ISBN: | 9783030950965 |
Internformat
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV049019495 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 230626s2022 |||| o||u| ||||||eng d | ||
| 020 | |a 9783030950965 |9 978-3-030-95096-5 | ||
| 035 | |a (ZDB-30-PQE)EBC6977297 | ||
| 035 | |a (ZDB-30-PAD)EBC6977297 | ||
| 035 | |a (ZDB-89-EBL)EBL6977297 | ||
| 035 | |a (OCoLC)1315744558 | ||
| 035 | |a (DE-599)BVBBV049019495 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-2070s | ||
| 082 | 0 | |a 332.10681 | |
| 084 | |a QK 320 |0 (DE-625)141644: |2 rvk | ||
| 100 | 1 | |a Bolder, David Jamieson |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Modelling Economic Capital |b Practical Credit-Risk Methodologies, Applications, and Implementation Details |
| 250 | |a 1st ed | ||
| 264 | 1 | |a Cham |b Springer International Publishing AG |c 2022 | |
| 264 | 4 | |c ©2022 | |
| 300 | |a 1 Online-Ressource (841 Seiten) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a Contributions to Finance and Accounting Series | |
| 500 | |a Description based on publisher supplied metadata and other sources | ||
| 505 | 8 | |a Intro -- Foreword -- Preface -- An Analyst's Objectives -- Analytic Axioms -- #1: Multiplicity of Perspective -- #2: Many Eyes -- #3: Pictures and Words -- #4: The Three Little Pigs -- #5: The Best for Last -- Why This Book? -- Acknowledgements -- References -- Testimonials -- Contents -- 1 Introducing Economic Capital -- 1.1 Presenting the Nordic Investment Bank -- 1.2 Defining Capital -- 1.2.1 The Risk Perspective -- 1.2.2 Capital Supply and Demand -- 1.3 An Enormous Simplification -- 1.4 Categorizing Risk -- 1.5 Risk Fundamentals -- 1.5.1 Two Silly Games -- 1.5.2 A Fundamental Characterization -- 1.5.3 Introducing Concentration -- 1.5.4 Modelling 101 -- 1.6 Managing Models -- 1.7 NIB's Portfolio -- 1.8 Looking Forward -- 1.9 Wrapping Up -- References -- Part I Modelling Credit-Risk Economic Capital -- 2 Constructing a Practical Model -- 2.1 A Naive, but Informative, Start -- 2.2 Mixture and Threshold Models -- 2.2.1 The Mixture Model -- 2.2.2 The Threshold Model -- 2.3 Asset-Return Dynamics -- 2.3.1 Time Discretization -- 2.3.2 Normalization -- 2.3.3 A Matrix Formulation -- 2.3.4 Orthogonalization -- 2.4 The Legacy Model -- 2.4.1 Introducing Default -- 2.4.2 Stochastic Recovery -- 2.4.3 Risk Metrics -- 2.5 Extending the Legacy Model -- 2.5.1 Changing the Copula -- 2.5.2 Constructing the t Copula -- 2.5.3 Default Correlation -- 2.5.4 Modelling Credit Migration -- 2.5.5 The Nuts and Bolts of Credit Migration -- 2.6 Risk Attribution -- 2.6.1 The Simplest Case -- 2.6.2 An Important Relationship -- 2.6.3 The Computational Path -- 2.6.4 A Clever Trick -- 2.7 Wrapping Up -- References -- 3 Finding Model Parameters -- 3.1 Credit States -- 3.1.1 Defining Credit Ratings -- 3.1.2 Transition Matrices -- 3.1.3 Default Probabilities -- 3.2 Systemic Factors -- 3.2.1 Factor Choice -- 3.2.2 Systemic-Factor Correlations -- Which Matrix? | |
| 505 | 8 | |a Which Correlation Measure? -- What Time Period? -- 3.2.3 Distinguishing Systemic Weights and Factor Loadings -- 3.2.4 Systemic-Factor Loadings -- Some Key Principles -- A Loading Estimation Approach -- A Simplifying Assumption -- Normalization -- 3.2.5 Systemic Weights -- A Systemic-Weight Dataset -- Estimating Correlations -- Imposing Strict Monotonicity -- A Final Look -- 3.3 A Portfolio Perspective -- 3.3.1 Systemic Proportions -- 3.3.2 Factor-, Asset-, and Default-Correlation -- 3.3.3 Tail Dependence -- 3.4 Recovery Rates -- 3.5 Credit Migration -- 3.5.1 Spread Duration -- 3.5.2 Credit Spreads -- The Theory -- Pricing Credit Risky Instruments -- The Credit-Spread Model -- Credit-Spread Estimation -- 3.6 Wrapping Up -- References -- 4 Implementing the Model -- 4.1 Managing Expectations -- 4.2 A System Architecture -- 4.3 The Data Layer -- 4.3.1 Key Data Inputs -- Peculiarities of Loan Exposures -- 4.4 The Application Layer -- 4.4.1 Purchase or Build Application Software? -- 4.4.2 Which Programming Environment? -- 4.4.3 The Application Environment -- 4.4.4 A High-Level Code Overview -- 4.4.5 Book-Keeping and Parameter Assignment -- 4.4.6 The Simulation Engine -- 4.5 Convergence -- 4.5.1 Constructing Confidence Bands -- 4.5.2 Portfolio-Level Convergence -- 4.5.3 Obligor-Level Convergence -- 4.5.4 Computational Expense -- 4.5.5 Choosing M -- 4.6 Wrapping Up -- References -- Part II Loan Pricing -- 5 Approximating Economic Capital -- 5.1 Framing the Problem -- 5.2 Approximating Default Economic Capital -- 5.2.1 Exploiting Existing Knowledge -- 5.2.2 Borrowing from Regulatory Guidance -- 5.2.3 A First Default Approximation Model -- 5.2.4 Incorporating Concentration -- 5.2.5 The Full Default Model -- 5.3 Approximating Migration Economic Capital -- 5.3.1 Conditional Migration Loss -- 5.3.2 A First Migration Model -- 5.3.3 The Full Migration Model | |
| 505 | 8 | |a 5.4 Approximation Model Due Diligence -- 5.5 The Full Picture -- 5.5.1 A Word on Implementation -- 5.5.2 An Immediate Application -- 5.6 Wrapping Up -- References -- 6 Loan Pricing -- 6.1 Some Fundamentals -- 6.2 A Holistic Perspective -- 6.2.1 The Balance-Sheet Perspective -- 6.2.2 Building the Foundation -- 6.3 Estimating Marginal Asset Income -- 6.3.1 Weighting Financing Sources -- 6.3.2 Other Income and Expenses -- 6.4 Risk-Adjusted Returns -- 6.5 The Hurdle Rate -- 6.6 Allocating Economic Capital -- 6.7 Getting More Practical -- 6.7.1 Immediate Disbursement -- 6.7.2 Payment Frequency -- 6.7.3 The Lending Margin -- 6.7.4 Existing Loan Exposure -- 6.7.5 Forward-Starting Disbursements -- 6.7.6 Selecting Commitment Fees -- 6.8 Wrapping Up -- References -- Part III Modelling Expected Credit Loss -- 7 Default-Probability Fundamentals -- 7.1 The Basics -- 7.1.1 The Limiting Case -- 7.1.2 An Extended Aside -- 7.2 A Thorny Problem -- 7.2.1 Set-Up -- 7.2.2 Some Theory -- 7.2.3 Regularization -- 7.2.4 Going to the Data -- 7.3 Building Default-Probability Surfaces -- 7.3.1 A Low-Dimensional Markov Chain -- 7.3.2 A Borrowed Model -- 7.3.3 Time Homogeneity -- 7.3.4 A Final Decisive Factor -- 7.4 Mapping to One's Master Scale -- 7.4.1 Building an Internal Default Probability Surface -- 7.4.2 Building an Internal Transition Matrix -- 7.5 Wrapping Up -- References -- 8 Building Stress Scenarios -- 8.1 Our Response Variables -- 8.1.1 Simplifying Matters -- 8.1.2 Introducing the Default Curve -- 8.1.3 Fitting Default Curves -- 8.2 Our Explanatory Variables -- 8.2.1 Data Issues -- 8.3 An Empirically Motivated Approach -- 8.3.1 A Linear Model -- 8.3.2 An Indirect Approach -- 8.3.3 An Alternative Formulation -- 8.3.4 A Short Aside -- 8.3.5 Building a Point-in-Time Transition Matrix -- The Role of P -- Upgrades and Downgrades -- Building h | |
| 505 | 8 | |a 8.4 A Theoretically Motivated Approach -- 8.4.1 Familiar Terrain -- 8.4.2 Yang:2017's Contribution -- 8.4.3 Adding Time -- 8.4.4 Parameter Estimation -- Preparation -- The First Step -- 8.4.5 The Second Step -- 8.4.6 To a Point-in-Time Transition Matrix -- 8.5 Constructing Default-Stress Scenarios -- 8.6 Wrapping Up -- References -- 9 Computing Loan Impairments -- 9.1 The Calculation -- 9.1.1 Defining Credit Loss -- 9.1.2 Selecting a Probability Measure -- 9.1.3 Managing the Time Horizon -- Time-Frequency, Interpolation and Bootstrapping -- 9.1.4 The Simplest Example -- 9.1.5 A More Realistic Example -- 9.1.6 Coupon and Discount Rates -- 9.1.7 Impact of Credit Rating -- 9.1.8 Adding Macro-Financial Uncertainty -- 9.1.9 Tying It All Together -- 9.2 Introducing Stages -- 9.2.1 Stage-Allocation Consequences -- 9.2.2 Stage-Allocation Logic -- 9.3 Managing Portfolio Composition -- 9.3.1 Motivating Our Adjustment -- 9.3.2 Building an Adjustment -- 9.3.3 Retiring Our Concrete Example -- 9.4 Wrapping Up -- References -- Part IV Other Practical Topics -- 10 Measuring Derivative Exposure -- 10.1 The Big Picture -- 10.2 Some Important Definitions -- 10.3 An Important Choice -- 10.4 A General, But Simplified Structure -- 10.4.1 Expected Exposure -- 10.4.2 Expected Positive Exposure -- 10.4.3 Potential Future Exposure -- 10.5 The Regulatory Approach -- 10.5.1 Replacement Cost -- 10.5.2 The Add-On -- 10.5.3 The Trade Level -- 10.5.4 The Multiplier -- 10.5.5 Bringing It All Together -- 10.6 The Asset-Class Perspective -- 10.6.1 Interest Rates -- 10.6.2 Currencies -- 10.7 A Pair of Practical Applications -- 10.7.1 Normalized Derivative Exposures -- 10.7.2 Defining and Measuring Leverage -- 10.8 Wrapping Up -- References -- 11 Seeking External Comparison -- 11.1 Pillar I -- 11.1.1 The Standardized Regulatory Approach -- 11.1.2 The Internal Ratings-Based Approach | |
| 505 | 8 | |a 11.1.3 S& -- P's Approach to Risk-Weighting -- 11.1.4 Risk-Weighted Assets -- 11.2 Pillar II -- 11.2.1 Geographic and Industrial Diversification -- Fisher's z-Transformation -- 11.2.2 Preferred-Creditor Treatment -- 11.2.3 Single-Name Concentration -- A First Try -- A Complicated Add-On -- The CreditRisk+ Case -- 11.2.4 Working with Partial Information -- 11.2.5 A Multi-Factor Adjustment -- A Generic Multi-Factor Model -- Introducing a One-Factor Model -- Calibrating the Multi- and Single-Factor Worlds -- Granularity Adjustment Revisited -- The Big Reveal -- The Drudgery -- 11.2.6 Practical Granularity-Adjustment Results -- 11.3 Wrapping Up -- References -- 12 Thoughts on Stress Testing -- 12.1 Organizing Stress-Testing -- 12.1.1 The Main Risk Pathway -- 12.1.2 Competing Approaches -- 12.1.3 Managing Time -- 12.1.4 Remaining Gameplan -- 12.2 The Top-Down, or Macro, Approach -- 12.2.1 Introducing the Vector Auto-Regressive Model -- 12.2.2 The Basic Idea -- 12.2.3 An Important Link -- 12.2.4 The Impulse-Response Function -- 12.2.5 A Base Sample Portfolio -- 12.2.6 From Macro Shock to Our Portfolio -- 12.2.7 The Portfolio Consequences -- 12.3 The Bottom-Up, or Micro, Approach -- 12.3.1 The Limits of Brute Force -- 12.3.2 The Extreme Cases -- 12.3.3 Traditional Bottom-Up Cases -- 12.3.4 Randomization -- 12.3.5 Collecting Our Bottom-Up Alternatives -- 12.4 Wrapping Up -- References -- Index -- Author Index | |
| 650 | 4 | |a Financial risk management | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |a Bolder, David Jamieson |t Modelling Economic Capital |d Cham : Springer International Publishing AG,c2022 |z 9783030950958 |
| 912 | |a ZDB-30-PQE | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-034282402 | ||
| 966 | e | |u https://ebookcentral.proquest.com/lib/hwr/detail.action?docID=6977297 |l HWR01 |p ZDB-30-PQE |q HWR_PDA_PQE |x Aggregator |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804185295616212992 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Bolder, David Jamieson |
| author_facet | Bolder, David Jamieson |
| author_role | aut |
| author_sort | Bolder, David Jamieson |
| author_variant | d j b dj djb |
| building | Verbundindex |
| bvnumber | BV049019495 |
| classification_rvk | QK 320 |
| collection | ZDB-30-PQE |
| contents | Intro -- Foreword -- Preface -- An Analyst's Objectives -- Analytic Axioms -- #1: Multiplicity of Perspective -- #2: Many Eyes -- #3: Pictures and Words -- #4: The Three Little Pigs -- #5: The Best for Last -- Why This Book? -- Acknowledgements -- References -- Testimonials -- Contents -- 1 Introducing Economic Capital -- 1.1 Presenting the Nordic Investment Bank -- 1.2 Defining Capital -- 1.2.1 The Risk Perspective -- 1.2.2 Capital Supply and Demand -- 1.3 An Enormous Simplification -- 1.4 Categorizing Risk -- 1.5 Risk Fundamentals -- 1.5.1 Two Silly Games -- 1.5.2 A Fundamental Characterization -- 1.5.3 Introducing Concentration -- 1.5.4 Modelling 101 -- 1.6 Managing Models -- 1.7 NIB's Portfolio -- 1.8 Looking Forward -- 1.9 Wrapping Up -- References -- Part I Modelling Credit-Risk Economic Capital -- 2 Constructing a Practical Model -- 2.1 A Naive, but Informative, Start -- 2.2 Mixture and Threshold Models -- 2.2.1 The Mixture Model -- 2.2.2 The Threshold Model -- 2.3 Asset-Return Dynamics -- 2.3.1 Time Discretization -- 2.3.2 Normalization -- 2.3.3 A Matrix Formulation -- 2.3.4 Orthogonalization -- 2.4 The Legacy Model -- 2.4.1 Introducing Default -- 2.4.2 Stochastic Recovery -- 2.4.3 Risk Metrics -- 2.5 Extending the Legacy Model -- 2.5.1 Changing the Copula -- 2.5.2 Constructing the t Copula -- 2.5.3 Default Correlation -- 2.5.4 Modelling Credit Migration -- 2.5.5 The Nuts and Bolts of Credit Migration -- 2.6 Risk Attribution -- 2.6.1 The Simplest Case -- 2.6.2 An Important Relationship -- 2.6.3 The Computational Path -- 2.6.4 A Clever Trick -- 2.7 Wrapping Up -- References -- 3 Finding Model Parameters -- 3.1 Credit States -- 3.1.1 Defining Credit Ratings -- 3.1.2 Transition Matrices -- 3.1.3 Default Probabilities -- 3.2 Systemic Factors -- 3.2.1 Factor Choice -- 3.2.2 Systemic-Factor Correlations -- Which Matrix? Which Correlation Measure? -- What Time Period? -- 3.2.3 Distinguishing Systemic Weights and Factor Loadings -- 3.2.4 Systemic-Factor Loadings -- Some Key Principles -- A Loading Estimation Approach -- A Simplifying Assumption -- Normalization -- 3.2.5 Systemic Weights -- A Systemic-Weight Dataset -- Estimating Correlations -- Imposing Strict Monotonicity -- A Final Look -- 3.3 A Portfolio Perspective -- 3.3.1 Systemic Proportions -- 3.3.2 Factor-, Asset-, and Default-Correlation -- 3.3.3 Tail Dependence -- 3.4 Recovery Rates -- 3.5 Credit Migration -- 3.5.1 Spread Duration -- 3.5.2 Credit Spreads -- The Theory -- Pricing Credit Risky Instruments -- The Credit-Spread Model -- Credit-Spread Estimation -- 3.6 Wrapping Up -- References -- 4 Implementing the Model -- 4.1 Managing Expectations -- 4.2 A System Architecture -- 4.3 The Data Layer -- 4.3.1 Key Data Inputs -- Peculiarities of Loan Exposures -- 4.4 The Application Layer -- 4.4.1 Purchase or Build Application Software? -- 4.4.2 Which Programming Environment? -- 4.4.3 The Application Environment -- 4.4.4 A High-Level Code Overview -- 4.4.5 Book-Keeping and Parameter Assignment -- 4.4.6 The Simulation Engine -- 4.5 Convergence -- 4.5.1 Constructing Confidence Bands -- 4.5.2 Portfolio-Level Convergence -- 4.5.3 Obligor-Level Convergence -- 4.5.4 Computational Expense -- 4.5.5 Choosing M -- 4.6 Wrapping Up -- References -- Part II Loan Pricing -- 5 Approximating Economic Capital -- 5.1 Framing the Problem -- 5.2 Approximating Default Economic Capital -- 5.2.1 Exploiting Existing Knowledge -- 5.2.2 Borrowing from Regulatory Guidance -- 5.2.3 A First Default Approximation Model -- 5.2.4 Incorporating Concentration -- 5.2.5 The Full Default Model -- 5.3 Approximating Migration Economic Capital -- 5.3.1 Conditional Migration Loss -- 5.3.2 A First Migration Model -- 5.3.3 The Full Migration Model 5.4 Approximation Model Due Diligence -- 5.5 The Full Picture -- 5.5.1 A Word on Implementation -- 5.5.2 An Immediate Application -- 5.6 Wrapping Up -- References -- 6 Loan Pricing -- 6.1 Some Fundamentals -- 6.2 A Holistic Perspective -- 6.2.1 The Balance-Sheet Perspective -- 6.2.2 Building the Foundation -- 6.3 Estimating Marginal Asset Income -- 6.3.1 Weighting Financing Sources -- 6.3.2 Other Income and Expenses -- 6.4 Risk-Adjusted Returns -- 6.5 The Hurdle Rate -- 6.6 Allocating Economic Capital -- 6.7 Getting More Practical -- 6.7.1 Immediate Disbursement -- 6.7.2 Payment Frequency -- 6.7.3 The Lending Margin -- 6.7.4 Existing Loan Exposure -- 6.7.5 Forward-Starting Disbursements -- 6.7.6 Selecting Commitment Fees -- 6.8 Wrapping Up -- References -- Part III Modelling Expected Credit Loss -- 7 Default-Probability Fundamentals -- 7.1 The Basics -- 7.1.1 The Limiting Case -- 7.1.2 An Extended Aside -- 7.2 A Thorny Problem -- 7.2.1 Set-Up -- 7.2.2 Some Theory -- 7.2.3 Regularization -- 7.2.4 Going to the Data -- 7.3 Building Default-Probability Surfaces -- 7.3.1 A Low-Dimensional Markov Chain -- 7.3.2 A Borrowed Model -- 7.3.3 Time Homogeneity -- 7.3.4 A Final Decisive Factor -- 7.4 Mapping to One's Master Scale -- 7.4.1 Building an Internal Default Probability Surface -- 7.4.2 Building an Internal Transition Matrix -- 7.5 Wrapping Up -- References -- 8 Building Stress Scenarios -- 8.1 Our Response Variables -- 8.1.1 Simplifying Matters -- 8.1.2 Introducing the Default Curve -- 8.1.3 Fitting Default Curves -- 8.2 Our Explanatory Variables -- 8.2.1 Data Issues -- 8.3 An Empirically Motivated Approach -- 8.3.1 A Linear Model -- 8.3.2 An Indirect Approach -- 8.3.3 An Alternative Formulation -- 8.3.4 A Short Aside -- 8.3.5 Building a Point-in-Time Transition Matrix -- The Role of P -- Upgrades and Downgrades -- Building h 8.4 A Theoretically Motivated Approach -- 8.4.1 Familiar Terrain -- 8.4.2 Yang:2017's Contribution -- 8.4.3 Adding Time -- 8.4.4 Parameter Estimation -- Preparation -- The First Step -- 8.4.5 The Second Step -- 8.4.6 To a Point-in-Time Transition Matrix -- 8.5 Constructing Default-Stress Scenarios -- 8.6 Wrapping Up -- References -- 9 Computing Loan Impairments -- 9.1 The Calculation -- 9.1.1 Defining Credit Loss -- 9.1.2 Selecting a Probability Measure -- 9.1.3 Managing the Time Horizon -- Time-Frequency, Interpolation and Bootstrapping -- 9.1.4 The Simplest Example -- 9.1.5 A More Realistic Example -- 9.1.6 Coupon and Discount Rates -- 9.1.7 Impact of Credit Rating -- 9.1.8 Adding Macro-Financial Uncertainty -- 9.1.9 Tying It All Together -- 9.2 Introducing Stages -- 9.2.1 Stage-Allocation Consequences -- 9.2.2 Stage-Allocation Logic -- 9.3 Managing Portfolio Composition -- 9.3.1 Motivating Our Adjustment -- 9.3.2 Building an Adjustment -- 9.3.3 Retiring Our Concrete Example -- 9.4 Wrapping Up -- References -- Part IV Other Practical Topics -- 10 Measuring Derivative Exposure -- 10.1 The Big Picture -- 10.2 Some Important Definitions -- 10.3 An Important Choice -- 10.4 A General, But Simplified Structure -- 10.4.1 Expected Exposure -- 10.4.2 Expected Positive Exposure -- 10.4.3 Potential Future Exposure -- 10.5 The Regulatory Approach -- 10.5.1 Replacement Cost -- 10.5.2 The Add-On -- 10.5.3 The Trade Level -- 10.5.4 The Multiplier -- 10.5.5 Bringing It All Together -- 10.6 The Asset-Class Perspective -- 10.6.1 Interest Rates -- 10.6.2 Currencies -- 10.7 A Pair of Practical Applications -- 10.7.1 Normalized Derivative Exposures -- 10.7.2 Defining and Measuring Leverage -- 10.8 Wrapping Up -- References -- 11 Seeking External Comparison -- 11.1 Pillar I -- 11.1.1 The Standardized Regulatory Approach -- 11.1.2 The Internal Ratings-Based Approach 11.1.3 S& -- P's Approach to Risk-Weighting -- 11.1.4 Risk-Weighted Assets -- 11.2 Pillar II -- 11.2.1 Geographic and Industrial Diversification -- Fisher's z-Transformation -- 11.2.2 Preferred-Creditor Treatment -- 11.2.3 Single-Name Concentration -- A First Try -- A Complicated Add-On -- The CreditRisk+ Case -- 11.2.4 Working with Partial Information -- 11.2.5 A Multi-Factor Adjustment -- A Generic Multi-Factor Model -- Introducing a One-Factor Model -- Calibrating the Multi- and Single-Factor Worlds -- Granularity Adjustment Revisited -- The Big Reveal -- The Drudgery -- 11.2.6 Practical Granularity-Adjustment Results -- 11.3 Wrapping Up -- References -- 12 Thoughts on Stress Testing -- 12.1 Organizing Stress-Testing -- 12.1.1 The Main Risk Pathway -- 12.1.2 Competing Approaches -- 12.1.3 Managing Time -- 12.1.4 Remaining Gameplan -- 12.2 The Top-Down, or Macro, Approach -- 12.2.1 Introducing the Vector Auto-Regressive Model -- 12.2.2 The Basic Idea -- 12.2.3 An Important Link -- 12.2.4 The Impulse-Response Function -- 12.2.5 A Base Sample Portfolio -- 12.2.6 From Macro Shock to Our Portfolio -- 12.2.7 The Portfolio Consequences -- 12.3 The Bottom-Up, or Micro, Approach -- 12.3.1 The Limits of Brute Force -- 12.3.2 The Extreme Cases -- 12.3.3 Traditional Bottom-Up Cases -- 12.3.4 Randomization -- 12.3.5 Collecting Our Bottom-Up Alternatives -- 12.4 Wrapping Up -- References -- Index -- Author Index |
| ctrlnum | (ZDB-30-PQE)EBC6977297 (ZDB-30-PAD)EBC6977297 (ZDB-89-EBL)EBL6977297 (OCoLC)1315744558 (DE-599)BVBBV049019495 |
| dewey-full | 332.10681 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 332 - Financial economics |
| dewey-raw | 332.10681 |
| dewey-search | 332.10681 |
| dewey-sort | 3332.10681 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| edition | 1st ed |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>10538nmm a2200469zc 4500</leader><controlfield tag="001">BV049019495</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">230626s2022 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783030950965</subfield><subfield code="9">978-3-030-95096-5</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-30-PQE)EBC6977297</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-30-PAD)EBC6977297</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-89-EBL)EBL6977297</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1315744558</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV049019495</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-2070s</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">332.10681</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">QK 320</subfield><subfield code="0">(DE-625)141644:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Bolder, David Jamieson</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Modelling Economic Capital</subfield><subfield code="b">Practical Credit-Risk Methodologies, Applications, and Implementation Details</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1st ed</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cham</subfield><subfield code="b">Springer International Publishing AG</subfield><subfield code="c">2022</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">©2022</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (841 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Contributions to Finance and Accounting Series</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Description based on publisher supplied metadata and other sources</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Intro -- Foreword -- Preface -- An Analyst's Objectives -- Analytic Axioms -- #1: Multiplicity of Perspective -- #2: Many Eyes -- #3: Pictures and Words -- #4: The Three Little Pigs -- #5: The Best for Last -- Why This Book? -- Acknowledgements -- References -- Testimonials -- Contents -- 1 Introducing Economic Capital -- 1.1 Presenting the Nordic Investment Bank -- 1.2 Defining Capital -- 1.2.1 The Risk Perspective -- 1.2.2 Capital Supply and Demand -- 1.3 An Enormous Simplification -- 1.4 Categorizing Risk -- 1.5 Risk Fundamentals -- 1.5.1 Two Silly Games -- 1.5.2 A Fundamental Characterization -- 1.5.3 Introducing Concentration -- 1.5.4 Modelling 101 -- 1.6 Managing Models -- 1.7 NIB's Portfolio -- 1.8 Looking Forward -- 1.9 Wrapping Up -- References -- Part I Modelling Credit-Risk Economic Capital -- 2 Constructing a Practical Model -- 2.1 A Naive, but Informative, Start -- 2.2 Mixture and Threshold Models -- 2.2.1 The Mixture Model -- 2.2.2 The Threshold Model -- 2.3 Asset-Return Dynamics -- 2.3.1 Time Discretization -- 2.3.2 Normalization -- 2.3.3 A Matrix Formulation -- 2.3.4 Orthogonalization -- 2.4 The Legacy Model -- 2.4.1 Introducing Default -- 2.4.2 Stochastic Recovery -- 2.4.3 Risk Metrics -- 2.5 Extending the Legacy Model -- 2.5.1 Changing the Copula -- 2.5.2 Constructing the t Copula -- 2.5.3 Default Correlation -- 2.5.4 Modelling Credit Migration -- 2.5.5 The Nuts and Bolts of Credit Migration -- 2.6 Risk Attribution -- 2.6.1 The Simplest Case -- 2.6.2 An Important Relationship -- 2.6.3 The Computational Path -- 2.6.4 A Clever Trick -- 2.7 Wrapping Up -- References -- 3 Finding Model Parameters -- 3.1 Credit States -- 3.1.1 Defining Credit Ratings -- 3.1.2 Transition Matrices -- 3.1.3 Default Probabilities -- 3.2 Systemic Factors -- 3.2.1 Factor Choice -- 3.2.2 Systemic-Factor Correlations -- Which Matrix?</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Which Correlation Measure? -- What Time Period? -- 3.2.3 Distinguishing Systemic Weights and Factor Loadings -- 3.2.4 Systemic-Factor Loadings -- Some Key Principles -- A Loading Estimation Approach -- A Simplifying Assumption -- Normalization -- 3.2.5 Systemic Weights -- A Systemic-Weight Dataset -- Estimating Correlations -- Imposing Strict Monotonicity -- A Final Look -- 3.3 A Portfolio Perspective -- 3.3.1 Systemic Proportions -- 3.3.2 Factor-, Asset-, and Default-Correlation -- 3.3.3 Tail Dependence -- 3.4 Recovery Rates -- 3.5 Credit Migration -- 3.5.1 Spread Duration -- 3.5.2 Credit Spreads -- The Theory -- Pricing Credit Risky Instruments -- The Credit-Spread Model -- Credit-Spread Estimation -- 3.6 Wrapping Up -- References -- 4 Implementing the Model -- 4.1 Managing Expectations -- 4.2 A System Architecture -- 4.3 The Data Layer -- 4.3.1 Key Data Inputs -- Peculiarities of Loan Exposures -- 4.4 The Application Layer -- 4.4.1 Purchase or Build Application Software? -- 4.4.2 Which Programming Environment? -- 4.4.3 The Application Environment -- 4.4.4 A High-Level Code Overview -- 4.4.5 Book-Keeping and Parameter Assignment -- 4.4.6 The Simulation Engine -- 4.5 Convergence -- 4.5.1 Constructing Confidence Bands -- 4.5.2 Portfolio-Level Convergence -- 4.5.3 Obligor-Level Convergence -- 4.5.4 Computational Expense -- 4.5.5 Choosing M -- 4.6 Wrapping Up -- References -- Part II Loan Pricing -- 5 Approximating Economic Capital -- 5.1 Framing the Problem -- 5.2 Approximating Default Economic Capital -- 5.2.1 Exploiting Existing Knowledge -- 5.2.2 Borrowing from Regulatory Guidance -- 5.2.3 A First Default Approximation Model -- 5.2.4 Incorporating Concentration -- 5.2.5 The Full Default Model -- 5.3 Approximating Migration Economic Capital -- 5.3.1 Conditional Migration Loss -- 5.3.2 A First Migration Model -- 5.3.3 The Full Migration Model</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">5.4 Approximation Model Due Diligence -- 5.5 The Full Picture -- 5.5.1 A Word on Implementation -- 5.5.2 An Immediate Application -- 5.6 Wrapping Up -- References -- 6 Loan Pricing -- 6.1 Some Fundamentals -- 6.2 A Holistic Perspective -- 6.2.1 The Balance-Sheet Perspective -- 6.2.2 Building the Foundation -- 6.3 Estimating Marginal Asset Income -- 6.3.1 Weighting Financing Sources -- 6.3.2 Other Income and Expenses -- 6.4 Risk-Adjusted Returns -- 6.5 The Hurdle Rate -- 6.6 Allocating Economic Capital -- 6.7 Getting More Practical -- 6.7.1 Immediate Disbursement -- 6.7.2 Payment Frequency -- 6.7.3 The Lending Margin -- 6.7.4 Existing Loan Exposure -- 6.7.5 Forward-Starting Disbursements -- 6.7.6 Selecting Commitment Fees -- 6.8 Wrapping Up -- References -- Part III Modelling Expected Credit Loss -- 7 Default-Probability Fundamentals -- 7.1 The Basics -- 7.1.1 The Limiting Case -- 7.1.2 An Extended Aside -- 7.2 A Thorny Problem -- 7.2.1 Set-Up -- 7.2.2 Some Theory -- 7.2.3 Regularization -- 7.2.4 Going to the Data -- 7.3 Building Default-Probability Surfaces -- 7.3.1 A Low-Dimensional Markov Chain -- 7.3.2 A Borrowed Model -- 7.3.3 Time Homogeneity -- 7.3.4 A Final Decisive Factor -- 7.4 Mapping to One's Master Scale -- 7.4.1 Building an Internal Default Probability Surface -- 7.4.2 Building an Internal Transition Matrix -- 7.5 Wrapping Up -- References -- 8 Building Stress Scenarios -- 8.1 Our Response Variables -- 8.1.1 Simplifying Matters -- 8.1.2 Introducing the Default Curve -- 8.1.3 Fitting Default Curves -- 8.2 Our Explanatory Variables -- 8.2.1 Data Issues -- 8.3 An Empirically Motivated Approach -- 8.3.1 A Linear Model -- 8.3.2 An Indirect Approach -- 8.3.3 An Alternative Formulation -- 8.3.4 A Short Aside -- 8.3.5 Building a Point-in-Time Transition Matrix -- The Role of P -- Upgrades and Downgrades -- Building h</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">8.4 A Theoretically Motivated Approach -- 8.4.1 Familiar Terrain -- 8.4.2 Yang:2017's Contribution -- 8.4.3 Adding Time -- 8.4.4 Parameter Estimation -- Preparation -- The First Step -- 8.4.5 The Second Step -- 8.4.6 To a Point-in-Time Transition Matrix -- 8.5 Constructing Default-Stress Scenarios -- 8.6 Wrapping Up -- References -- 9 Computing Loan Impairments -- 9.1 The Calculation -- 9.1.1 Defining Credit Loss -- 9.1.2 Selecting a Probability Measure -- 9.1.3 Managing the Time Horizon -- Time-Frequency, Interpolation and Bootstrapping -- 9.1.4 The Simplest Example -- 9.1.5 A More Realistic Example -- 9.1.6 Coupon and Discount Rates -- 9.1.7 Impact of Credit Rating -- 9.1.8 Adding Macro-Financial Uncertainty -- 9.1.9 Tying It All Together -- 9.2 Introducing Stages -- 9.2.1 Stage-Allocation Consequences -- 9.2.2 Stage-Allocation Logic -- 9.3 Managing Portfolio Composition -- 9.3.1 Motivating Our Adjustment -- 9.3.2 Building an Adjustment -- 9.3.3 Retiring Our Concrete Example -- 9.4 Wrapping Up -- References -- Part IV Other Practical Topics -- 10 Measuring Derivative Exposure -- 10.1 The Big Picture -- 10.2 Some Important Definitions -- 10.3 An Important Choice -- 10.4 A General, But Simplified Structure -- 10.4.1 Expected Exposure -- 10.4.2 Expected Positive Exposure -- 10.4.3 Potential Future Exposure -- 10.5 The Regulatory Approach -- 10.5.1 Replacement Cost -- 10.5.2 The Add-On -- 10.5.3 The Trade Level -- 10.5.4 The Multiplier -- 10.5.5 Bringing It All Together -- 10.6 The Asset-Class Perspective -- 10.6.1 Interest Rates -- 10.6.2 Currencies -- 10.7 A Pair of Practical Applications -- 10.7.1 Normalized Derivative Exposures -- 10.7.2 Defining and Measuring Leverage -- 10.8 Wrapping Up -- References -- 11 Seeking External Comparison -- 11.1 Pillar I -- 11.1.1 The Standardized Regulatory Approach -- 11.1.2 The Internal Ratings-Based Approach</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">11.1.3 S&amp -- P's Approach to Risk-Weighting -- 11.1.4 Risk-Weighted Assets -- 11.2 Pillar II -- 11.2.1 Geographic and Industrial Diversification -- Fisher's z-Transformation -- 11.2.2 Preferred-Creditor Treatment -- 11.2.3 Single-Name Concentration -- A First Try -- A Complicated Add-On -- The CreditRisk+ Case -- 11.2.4 Working with Partial Information -- 11.2.5 A Multi-Factor Adjustment -- A Generic Multi-Factor Model -- Introducing a One-Factor Model -- Calibrating the Multi- and Single-Factor Worlds -- Granularity Adjustment Revisited -- The Big Reveal -- The Drudgery -- 11.2.6 Practical Granularity-Adjustment Results -- 11.3 Wrapping Up -- References -- 12 Thoughts on Stress Testing -- 12.1 Organizing Stress-Testing -- 12.1.1 The Main Risk Pathway -- 12.1.2 Competing Approaches -- 12.1.3 Managing Time -- 12.1.4 Remaining Gameplan -- 12.2 The Top-Down, or Macro, Approach -- 12.2.1 Introducing the Vector Auto-Regressive Model -- 12.2.2 The Basic Idea -- 12.2.3 An Important Link -- 12.2.4 The Impulse-Response Function -- 12.2.5 A Base Sample Portfolio -- 12.2.6 From Macro Shock to Our Portfolio -- 12.2.7 The Portfolio Consequences -- 12.3 The Bottom-Up, or Micro, Approach -- 12.3.1 The Limits of Brute Force -- 12.3.2 The Extreme Cases -- 12.3.3 Traditional Bottom-Up Cases -- 12.3.4 Randomization -- 12.3.5 Collecting Our Bottom-Up Alternatives -- 12.4 Wrapping Up -- References -- Index -- Author Index</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Financial risk management</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="a">Bolder, David Jamieson</subfield><subfield code="t">Modelling Economic Capital</subfield><subfield code="d">Cham : Springer International Publishing AG,c2022</subfield><subfield code="z">9783030950958</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-PQE</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-034282402</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://ebookcentral.proquest.com/lib/hwr/detail.action?docID=6977297</subfield><subfield code="l">HWR01</subfield><subfield code="p">ZDB-30-PQE</subfield><subfield code="q">HWR_PDA_PQE</subfield><subfield code="x">Aggregator</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV049019495 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T22:13:39Z |
| indexdate | 2024-07-10T09:52:58Z |
| institution | BVB |
| isbn | 9783030950965 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034282402 |
| oclc_num | 1315744558 |
| open_access_boolean | |
| owner | DE-2070s |
| owner_facet | DE-2070s |
| physical | 1 Online-Ressource (841 Seiten) |
| psigel | ZDB-30-PQE ZDB-30-PQE HWR_PDA_PQE |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | Springer International Publishing AG |
| record_format | marc |
| series2 | Contributions to Finance and Accounting Series |
| spelling | Bolder, David Jamieson Verfasser aut Modelling Economic Capital Practical Credit-Risk Methodologies, Applications, and Implementation Details 1st ed Cham Springer International Publishing AG 2022 ©2022 1 Online-Ressource (841 Seiten) txt rdacontent c rdamedia cr rdacarrier Contributions to Finance and Accounting Series Description based on publisher supplied metadata and other sources Intro -- Foreword -- Preface -- An Analyst's Objectives -- Analytic Axioms -- #1: Multiplicity of Perspective -- #2: Many Eyes -- #3: Pictures and Words -- #4: The Three Little Pigs -- #5: The Best for Last -- Why This Book? -- Acknowledgements -- References -- Testimonials -- Contents -- 1 Introducing Economic Capital -- 1.1 Presenting the Nordic Investment Bank -- 1.2 Defining Capital -- 1.2.1 The Risk Perspective -- 1.2.2 Capital Supply and Demand -- 1.3 An Enormous Simplification -- 1.4 Categorizing Risk -- 1.5 Risk Fundamentals -- 1.5.1 Two Silly Games -- 1.5.2 A Fundamental Characterization -- 1.5.3 Introducing Concentration -- 1.5.4 Modelling 101 -- 1.6 Managing Models -- 1.7 NIB's Portfolio -- 1.8 Looking Forward -- 1.9 Wrapping Up -- References -- Part I Modelling Credit-Risk Economic Capital -- 2 Constructing a Practical Model -- 2.1 A Naive, but Informative, Start -- 2.2 Mixture and Threshold Models -- 2.2.1 The Mixture Model -- 2.2.2 The Threshold Model -- 2.3 Asset-Return Dynamics -- 2.3.1 Time Discretization -- 2.3.2 Normalization -- 2.3.3 A Matrix Formulation -- 2.3.4 Orthogonalization -- 2.4 The Legacy Model -- 2.4.1 Introducing Default -- 2.4.2 Stochastic Recovery -- 2.4.3 Risk Metrics -- 2.5 Extending the Legacy Model -- 2.5.1 Changing the Copula -- 2.5.2 Constructing the t Copula -- 2.5.3 Default Correlation -- 2.5.4 Modelling Credit Migration -- 2.5.5 The Nuts and Bolts of Credit Migration -- 2.6 Risk Attribution -- 2.6.1 The Simplest Case -- 2.6.2 An Important Relationship -- 2.6.3 The Computational Path -- 2.6.4 A Clever Trick -- 2.7 Wrapping Up -- References -- 3 Finding Model Parameters -- 3.1 Credit States -- 3.1.1 Defining Credit Ratings -- 3.1.2 Transition Matrices -- 3.1.3 Default Probabilities -- 3.2 Systemic Factors -- 3.2.1 Factor Choice -- 3.2.2 Systemic-Factor Correlations -- Which Matrix? Which Correlation Measure? -- What Time Period? -- 3.2.3 Distinguishing Systemic Weights and Factor Loadings -- 3.2.4 Systemic-Factor Loadings -- Some Key Principles -- A Loading Estimation Approach -- A Simplifying Assumption -- Normalization -- 3.2.5 Systemic Weights -- A Systemic-Weight Dataset -- Estimating Correlations -- Imposing Strict Monotonicity -- A Final Look -- 3.3 A Portfolio Perspective -- 3.3.1 Systemic Proportions -- 3.3.2 Factor-, Asset-, and Default-Correlation -- 3.3.3 Tail Dependence -- 3.4 Recovery Rates -- 3.5 Credit Migration -- 3.5.1 Spread Duration -- 3.5.2 Credit Spreads -- The Theory -- Pricing Credit Risky Instruments -- The Credit-Spread Model -- Credit-Spread Estimation -- 3.6 Wrapping Up -- References -- 4 Implementing the Model -- 4.1 Managing Expectations -- 4.2 A System Architecture -- 4.3 The Data Layer -- 4.3.1 Key Data Inputs -- Peculiarities of Loan Exposures -- 4.4 The Application Layer -- 4.4.1 Purchase or Build Application Software? -- 4.4.2 Which Programming Environment? -- 4.4.3 The Application Environment -- 4.4.4 A High-Level Code Overview -- 4.4.5 Book-Keeping and Parameter Assignment -- 4.4.6 The Simulation Engine -- 4.5 Convergence -- 4.5.1 Constructing Confidence Bands -- 4.5.2 Portfolio-Level Convergence -- 4.5.3 Obligor-Level Convergence -- 4.5.4 Computational Expense -- 4.5.5 Choosing M -- 4.6 Wrapping Up -- References -- Part II Loan Pricing -- 5 Approximating Economic Capital -- 5.1 Framing the Problem -- 5.2 Approximating Default Economic Capital -- 5.2.1 Exploiting Existing Knowledge -- 5.2.2 Borrowing from Regulatory Guidance -- 5.2.3 A First Default Approximation Model -- 5.2.4 Incorporating Concentration -- 5.2.5 The Full Default Model -- 5.3 Approximating Migration Economic Capital -- 5.3.1 Conditional Migration Loss -- 5.3.2 A First Migration Model -- 5.3.3 The Full Migration Model 5.4 Approximation Model Due Diligence -- 5.5 The Full Picture -- 5.5.1 A Word on Implementation -- 5.5.2 An Immediate Application -- 5.6 Wrapping Up -- References -- 6 Loan Pricing -- 6.1 Some Fundamentals -- 6.2 A Holistic Perspective -- 6.2.1 The Balance-Sheet Perspective -- 6.2.2 Building the Foundation -- 6.3 Estimating Marginal Asset Income -- 6.3.1 Weighting Financing Sources -- 6.3.2 Other Income and Expenses -- 6.4 Risk-Adjusted Returns -- 6.5 The Hurdle Rate -- 6.6 Allocating Economic Capital -- 6.7 Getting More Practical -- 6.7.1 Immediate Disbursement -- 6.7.2 Payment Frequency -- 6.7.3 The Lending Margin -- 6.7.4 Existing Loan Exposure -- 6.7.5 Forward-Starting Disbursements -- 6.7.6 Selecting Commitment Fees -- 6.8 Wrapping Up -- References -- Part III Modelling Expected Credit Loss -- 7 Default-Probability Fundamentals -- 7.1 The Basics -- 7.1.1 The Limiting Case -- 7.1.2 An Extended Aside -- 7.2 A Thorny Problem -- 7.2.1 Set-Up -- 7.2.2 Some Theory -- 7.2.3 Regularization -- 7.2.4 Going to the Data -- 7.3 Building Default-Probability Surfaces -- 7.3.1 A Low-Dimensional Markov Chain -- 7.3.2 A Borrowed Model -- 7.3.3 Time Homogeneity -- 7.3.4 A Final Decisive Factor -- 7.4 Mapping to One's Master Scale -- 7.4.1 Building an Internal Default Probability Surface -- 7.4.2 Building an Internal Transition Matrix -- 7.5 Wrapping Up -- References -- 8 Building Stress Scenarios -- 8.1 Our Response Variables -- 8.1.1 Simplifying Matters -- 8.1.2 Introducing the Default Curve -- 8.1.3 Fitting Default Curves -- 8.2 Our Explanatory Variables -- 8.2.1 Data Issues -- 8.3 An Empirically Motivated Approach -- 8.3.1 A Linear Model -- 8.3.2 An Indirect Approach -- 8.3.3 An Alternative Formulation -- 8.3.4 A Short Aside -- 8.3.5 Building a Point-in-Time Transition Matrix -- The Role of P -- Upgrades and Downgrades -- Building h 8.4 A Theoretically Motivated Approach -- 8.4.1 Familiar Terrain -- 8.4.2 Yang:2017's Contribution -- 8.4.3 Adding Time -- 8.4.4 Parameter Estimation -- Preparation -- The First Step -- 8.4.5 The Second Step -- 8.4.6 To a Point-in-Time Transition Matrix -- 8.5 Constructing Default-Stress Scenarios -- 8.6 Wrapping Up -- References -- 9 Computing Loan Impairments -- 9.1 The Calculation -- 9.1.1 Defining Credit Loss -- 9.1.2 Selecting a Probability Measure -- 9.1.3 Managing the Time Horizon -- Time-Frequency, Interpolation and Bootstrapping -- 9.1.4 The Simplest Example -- 9.1.5 A More Realistic Example -- 9.1.6 Coupon and Discount Rates -- 9.1.7 Impact of Credit Rating -- 9.1.8 Adding Macro-Financial Uncertainty -- 9.1.9 Tying It All Together -- 9.2 Introducing Stages -- 9.2.1 Stage-Allocation Consequences -- 9.2.2 Stage-Allocation Logic -- 9.3 Managing Portfolio Composition -- 9.3.1 Motivating Our Adjustment -- 9.3.2 Building an Adjustment -- 9.3.3 Retiring Our Concrete Example -- 9.4 Wrapping Up -- References -- Part IV Other Practical Topics -- 10 Measuring Derivative Exposure -- 10.1 The Big Picture -- 10.2 Some Important Definitions -- 10.3 An Important Choice -- 10.4 A General, But Simplified Structure -- 10.4.1 Expected Exposure -- 10.4.2 Expected Positive Exposure -- 10.4.3 Potential Future Exposure -- 10.5 The Regulatory Approach -- 10.5.1 Replacement Cost -- 10.5.2 The Add-On -- 10.5.3 The Trade Level -- 10.5.4 The Multiplier -- 10.5.5 Bringing It All Together -- 10.6 The Asset-Class Perspective -- 10.6.1 Interest Rates -- 10.6.2 Currencies -- 10.7 A Pair of Practical Applications -- 10.7.1 Normalized Derivative Exposures -- 10.7.2 Defining and Measuring Leverage -- 10.8 Wrapping Up -- References -- 11 Seeking External Comparison -- 11.1 Pillar I -- 11.1.1 The Standardized Regulatory Approach -- 11.1.2 The Internal Ratings-Based Approach 11.1.3 S& -- P's Approach to Risk-Weighting -- 11.1.4 Risk-Weighted Assets -- 11.2 Pillar II -- 11.2.1 Geographic and Industrial Diversification -- Fisher's z-Transformation -- 11.2.2 Preferred-Creditor Treatment -- 11.2.3 Single-Name Concentration -- A First Try -- A Complicated Add-On -- The CreditRisk+ Case -- 11.2.4 Working with Partial Information -- 11.2.5 A Multi-Factor Adjustment -- A Generic Multi-Factor Model -- Introducing a One-Factor Model -- Calibrating the Multi- and Single-Factor Worlds -- Granularity Adjustment Revisited -- The Big Reveal -- The Drudgery -- 11.2.6 Practical Granularity-Adjustment Results -- 11.3 Wrapping Up -- References -- 12 Thoughts on Stress Testing -- 12.1 Organizing Stress-Testing -- 12.1.1 The Main Risk Pathway -- 12.1.2 Competing Approaches -- 12.1.3 Managing Time -- 12.1.4 Remaining Gameplan -- 12.2 The Top-Down, or Macro, Approach -- 12.2.1 Introducing the Vector Auto-Regressive Model -- 12.2.2 The Basic Idea -- 12.2.3 An Important Link -- 12.2.4 The Impulse-Response Function -- 12.2.5 A Base Sample Portfolio -- 12.2.6 From Macro Shock to Our Portfolio -- 12.2.7 The Portfolio Consequences -- 12.3 The Bottom-Up, or Micro, Approach -- 12.3.1 The Limits of Brute Force -- 12.3.2 The Extreme Cases -- 12.3.3 Traditional Bottom-Up Cases -- 12.3.4 Randomization -- 12.3.5 Collecting Our Bottom-Up Alternatives -- 12.4 Wrapping Up -- References -- Index -- Author Index Financial risk management Erscheint auch als Druck-Ausgabe Bolder, David Jamieson Modelling Economic Capital Cham : Springer International Publishing AG,c2022 9783030950958 |
| spellingShingle | Bolder, David Jamieson Modelling Economic Capital Practical Credit-Risk Methodologies, Applications, and Implementation Details Intro -- Foreword -- Preface -- An Analyst's Objectives -- Analytic Axioms -- #1: Multiplicity of Perspective -- #2: Many Eyes -- #3: Pictures and Words -- #4: The Three Little Pigs -- #5: The Best for Last -- Why This Book? -- Acknowledgements -- References -- Testimonials -- Contents -- 1 Introducing Economic Capital -- 1.1 Presenting the Nordic Investment Bank -- 1.2 Defining Capital -- 1.2.1 The Risk Perspective -- 1.2.2 Capital Supply and Demand -- 1.3 An Enormous Simplification -- 1.4 Categorizing Risk -- 1.5 Risk Fundamentals -- 1.5.1 Two Silly Games -- 1.5.2 A Fundamental Characterization -- 1.5.3 Introducing Concentration -- 1.5.4 Modelling 101 -- 1.6 Managing Models -- 1.7 NIB's Portfolio -- 1.8 Looking Forward -- 1.9 Wrapping Up -- References -- Part I Modelling Credit-Risk Economic Capital -- 2 Constructing a Practical Model -- 2.1 A Naive, but Informative, Start -- 2.2 Mixture and Threshold Models -- 2.2.1 The Mixture Model -- 2.2.2 The Threshold Model -- 2.3 Asset-Return Dynamics -- 2.3.1 Time Discretization -- 2.3.2 Normalization -- 2.3.3 A Matrix Formulation -- 2.3.4 Orthogonalization -- 2.4 The Legacy Model -- 2.4.1 Introducing Default -- 2.4.2 Stochastic Recovery -- 2.4.3 Risk Metrics -- 2.5 Extending the Legacy Model -- 2.5.1 Changing the Copula -- 2.5.2 Constructing the t Copula -- 2.5.3 Default Correlation -- 2.5.4 Modelling Credit Migration -- 2.5.5 The Nuts and Bolts of Credit Migration -- 2.6 Risk Attribution -- 2.6.1 The Simplest Case -- 2.6.2 An Important Relationship -- 2.6.3 The Computational Path -- 2.6.4 A Clever Trick -- 2.7 Wrapping Up -- References -- 3 Finding Model Parameters -- 3.1 Credit States -- 3.1.1 Defining Credit Ratings -- 3.1.2 Transition Matrices -- 3.1.3 Default Probabilities -- 3.2 Systemic Factors -- 3.2.1 Factor Choice -- 3.2.2 Systemic-Factor Correlations -- Which Matrix? Which Correlation Measure? -- What Time Period? -- 3.2.3 Distinguishing Systemic Weights and Factor Loadings -- 3.2.4 Systemic-Factor Loadings -- Some Key Principles -- A Loading Estimation Approach -- A Simplifying Assumption -- Normalization -- 3.2.5 Systemic Weights -- A Systemic-Weight Dataset -- Estimating Correlations -- Imposing Strict Monotonicity -- A Final Look -- 3.3 A Portfolio Perspective -- 3.3.1 Systemic Proportions -- 3.3.2 Factor-, Asset-, and Default-Correlation -- 3.3.3 Tail Dependence -- 3.4 Recovery Rates -- 3.5 Credit Migration -- 3.5.1 Spread Duration -- 3.5.2 Credit Spreads -- The Theory -- Pricing Credit Risky Instruments -- The Credit-Spread Model -- Credit-Spread Estimation -- 3.6 Wrapping Up -- References -- 4 Implementing the Model -- 4.1 Managing Expectations -- 4.2 A System Architecture -- 4.3 The Data Layer -- 4.3.1 Key Data Inputs -- Peculiarities of Loan Exposures -- 4.4 The Application Layer -- 4.4.1 Purchase or Build Application Software? -- 4.4.2 Which Programming Environment? -- 4.4.3 The Application Environment -- 4.4.4 A High-Level Code Overview -- 4.4.5 Book-Keeping and Parameter Assignment -- 4.4.6 The Simulation Engine -- 4.5 Convergence -- 4.5.1 Constructing Confidence Bands -- 4.5.2 Portfolio-Level Convergence -- 4.5.3 Obligor-Level Convergence -- 4.5.4 Computational Expense -- 4.5.5 Choosing M -- 4.6 Wrapping Up -- References -- Part II Loan Pricing -- 5 Approximating Economic Capital -- 5.1 Framing the Problem -- 5.2 Approximating Default Economic Capital -- 5.2.1 Exploiting Existing Knowledge -- 5.2.2 Borrowing from Regulatory Guidance -- 5.2.3 A First Default Approximation Model -- 5.2.4 Incorporating Concentration -- 5.2.5 The Full Default Model -- 5.3 Approximating Migration Economic Capital -- 5.3.1 Conditional Migration Loss -- 5.3.2 A First Migration Model -- 5.3.3 The Full Migration Model 5.4 Approximation Model Due Diligence -- 5.5 The Full Picture -- 5.5.1 A Word on Implementation -- 5.5.2 An Immediate Application -- 5.6 Wrapping Up -- References -- 6 Loan Pricing -- 6.1 Some Fundamentals -- 6.2 A Holistic Perspective -- 6.2.1 The Balance-Sheet Perspective -- 6.2.2 Building the Foundation -- 6.3 Estimating Marginal Asset Income -- 6.3.1 Weighting Financing Sources -- 6.3.2 Other Income and Expenses -- 6.4 Risk-Adjusted Returns -- 6.5 The Hurdle Rate -- 6.6 Allocating Economic Capital -- 6.7 Getting More Practical -- 6.7.1 Immediate Disbursement -- 6.7.2 Payment Frequency -- 6.7.3 The Lending Margin -- 6.7.4 Existing Loan Exposure -- 6.7.5 Forward-Starting Disbursements -- 6.7.6 Selecting Commitment Fees -- 6.8 Wrapping Up -- References -- Part III Modelling Expected Credit Loss -- 7 Default-Probability Fundamentals -- 7.1 The Basics -- 7.1.1 The Limiting Case -- 7.1.2 An Extended Aside -- 7.2 A Thorny Problem -- 7.2.1 Set-Up -- 7.2.2 Some Theory -- 7.2.3 Regularization -- 7.2.4 Going to the Data -- 7.3 Building Default-Probability Surfaces -- 7.3.1 A Low-Dimensional Markov Chain -- 7.3.2 A Borrowed Model -- 7.3.3 Time Homogeneity -- 7.3.4 A Final Decisive Factor -- 7.4 Mapping to One's Master Scale -- 7.4.1 Building an Internal Default Probability Surface -- 7.4.2 Building an Internal Transition Matrix -- 7.5 Wrapping Up -- References -- 8 Building Stress Scenarios -- 8.1 Our Response Variables -- 8.1.1 Simplifying Matters -- 8.1.2 Introducing the Default Curve -- 8.1.3 Fitting Default Curves -- 8.2 Our Explanatory Variables -- 8.2.1 Data Issues -- 8.3 An Empirically Motivated Approach -- 8.3.1 A Linear Model -- 8.3.2 An Indirect Approach -- 8.3.3 An Alternative Formulation -- 8.3.4 A Short Aside -- 8.3.5 Building a Point-in-Time Transition Matrix -- The Role of P -- Upgrades and Downgrades -- Building h 8.4 A Theoretically Motivated Approach -- 8.4.1 Familiar Terrain -- 8.4.2 Yang:2017's Contribution -- 8.4.3 Adding Time -- 8.4.4 Parameter Estimation -- Preparation -- The First Step -- 8.4.5 The Second Step -- 8.4.6 To a Point-in-Time Transition Matrix -- 8.5 Constructing Default-Stress Scenarios -- 8.6 Wrapping Up -- References -- 9 Computing Loan Impairments -- 9.1 The Calculation -- 9.1.1 Defining Credit Loss -- 9.1.2 Selecting a Probability Measure -- 9.1.3 Managing the Time Horizon -- Time-Frequency, Interpolation and Bootstrapping -- 9.1.4 The Simplest Example -- 9.1.5 A More Realistic Example -- 9.1.6 Coupon and Discount Rates -- 9.1.7 Impact of Credit Rating -- 9.1.8 Adding Macro-Financial Uncertainty -- 9.1.9 Tying It All Together -- 9.2 Introducing Stages -- 9.2.1 Stage-Allocation Consequences -- 9.2.2 Stage-Allocation Logic -- 9.3 Managing Portfolio Composition -- 9.3.1 Motivating Our Adjustment -- 9.3.2 Building an Adjustment -- 9.3.3 Retiring Our Concrete Example -- 9.4 Wrapping Up -- References -- Part IV Other Practical Topics -- 10 Measuring Derivative Exposure -- 10.1 The Big Picture -- 10.2 Some Important Definitions -- 10.3 An Important Choice -- 10.4 A General, But Simplified Structure -- 10.4.1 Expected Exposure -- 10.4.2 Expected Positive Exposure -- 10.4.3 Potential Future Exposure -- 10.5 The Regulatory Approach -- 10.5.1 Replacement Cost -- 10.5.2 The Add-On -- 10.5.3 The Trade Level -- 10.5.4 The Multiplier -- 10.5.5 Bringing It All Together -- 10.6 The Asset-Class Perspective -- 10.6.1 Interest Rates -- 10.6.2 Currencies -- 10.7 A Pair of Practical Applications -- 10.7.1 Normalized Derivative Exposures -- 10.7.2 Defining and Measuring Leverage -- 10.8 Wrapping Up -- References -- 11 Seeking External Comparison -- 11.1 Pillar I -- 11.1.1 The Standardized Regulatory Approach -- 11.1.2 The Internal Ratings-Based Approach 11.1.3 S& -- P's Approach to Risk-Weighting -- 11.1.4 Risk-Weighted Assets -- 11.2 Pillar II -- 11.2.1 Geographic and Industrial Diversification -- Fisher's z-Transformation -- 11.2.2 Preferred-Creditor Treatment -- 11.2.3 Single-Name Concentration -- A First Try -- A Complicated Add-On -- The CreditRisk+ Case -- 11.2.4 Working with Partial Information -- 11.2.5 A Multi-Factor Adjustment -- A Generic Multi-Factor Model -- Introducing a One-Factor Model -- Calibrating the Multi- and Single-Factor Worlds -- Granularity Adjustment Revisited -- The Big Reveal -- The Drudgery -- 11.2.6 Practical Granularity-Adjustment Results -- 11.3 Wrapping Up -- References -- 12 Thoughts on Stress Testing -- 12.1 Organizing Stress-Testing -- 12.1.1 The Main Risk Pathway -- 12.1.2 Competing Approaches -- 12.1.3 Managing Time -- 12.1.4 Remaining Gameplan -- 12.2 The Top-Down, or Macro, Approach -- 12.2.1 Introducing the Vector Auto-Regressive Model -- 12.2.2 The Basic Idea -- 12.2.3 An Important Link -- 12.2.4 The Impulse-Response Function -- 12.2.5 A Base Sample Portfolio -- 12.2.6 From Macro Shock to Our Portfolio -- 12.2.7 The Portfolio Consequences -- 12.3 The Bottom-Up, or Micro, Approach -- 12.3.1 The Limits of Brute Force -- 12.3.2 The Extreme Cases -- 12.3.3 Traditional Bottom-Up Cases -- 12.3.4 Randomization -- 12.3.5 Collecting Our Bottom-Up Alternatives -- 12.4 Wrapping Up -- References -- Index -- Author Index Financial risk management |
| title | Modelling Economic Capital Practical Credit-Risk Methodologies, Applications, and Implementation Details |
| title_auth | Modelling Economic Capital Practical Credit-Risk Methodologies, Applications, and Implementation Details |
| title_exact_search | Modelling Economic Capital Practical Credit-Risk Methodologies, Applications, and Implementation Details |
| title_exact_search_txtP | Modelling Economic Capital Practical Credit-Risk Methodologies, Applications, and Implementation Details |
| title_full | Modelling Economic Capital Practical Credit-Risk Methodologies, Applications, and Implementation Details |
| title_fullStr | Modelling Economic Capital Practical Credit-Risk Methodologies, Applications, and Implementation Details |
| title_full_unstemmed | Modelling Economic Capital Practical Credit-Risk Methodologies, Applications, and Implementation Details |
| title_short | Modelling Economic Capital |
| title_sort | modelling economic capital practical credit risk methodologies applications and implementation details |
| title_sub | Practical Credit-Risk Methodologies, Applications, and Implementation Details |
| topic | Financial risk management |
| topic_facet | Financial risk management |
| work_keys_str_mv | AT bolderdavidjamieson modellingeconomiccapitalpracticalcreditriskmethodologiesapplicationsandimplementationdetails |